Single-Pathway DeepMedic

This repo is an reimplement of Single-Pathway DeepMedic.

Requirements

• The code has been written in Python 3.6.3 and Pytorch 1.0.1
• Make sure to install all the libraries given in requirement.txt, and you can do so by the following command

pip install -r requirement.txt

Dataset

We run experiments on BRATS 2015 Subset. It includes training set and testing set with lables. This subset has 20 brain turmor subjects for training and 54 subjects for testing, each of which includes four moldalities: FLAIR, T1, T1c, T2, and mask and ground truth. The ground truth of patient images have four different labels:

• label 1: necrosis
• label 2: edema
• label 3: non-enhancing tumor
• label 4: enhancing tumor
• label 0: everything else

The evaluation is done for 3 different tumor sub-compartements:

• Whole tumor: label 1, 2, 3, 4
• Enhance tumor: label 4
• Tumor core: 1, 3, 4

How to preprocess the dataset?

You can use generate_mask.ipynb to generate mask for each image.

How to run Single-Pathway DeepMedic?

Training and testing for Single-Pathway DeepMedic are written in Single_Pathway_DeepMedic.ipynb. If you have any question about the code, you can create a new issue.